The present disclosure relates to the field of probabilistic databases, and, more particularly, to probabilistic voxel-based database that driving different uncertainty-level dependent query and interface modes.
A probabilistic database is an uncertain database in which database records have associated probabilities. Probabilistic databases establish a data recording and querying methodology that provide a uniform approach for handling imprecision.
No current commercial probabilistic database systems exist; many research prototypes exist which include the MayBMS project at Cornell University, the MystiQ project at the University of Washington, the Orion project at Purdue University, and the Trio project at Stanford University. Current projects use probabilistic versions of conditional tables as an encoding mechanism for uncertainty handling. Consequently, incoming information is handled in a standard way, where additional overhead is added for expressing uncertainty, which is an inherently inefficient representation scheme that adds substantial storage overhead.
No known probabilistic database has been used within a geospatial information system (GIS) to handle geospatial data. No known set of geospatial end-user interfaces present geospatial content in a variable manner that visually corresponds to different uncertainty levels of geospatial data.